Attention-based view on achieving ambidexterity in purchasing and supply management

Harri Lorentz*, Sini Laari, Janne Engblom, Kari Tanskanen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)


The focus of purchasing and supply management (PSM) is no longer just on short-term cost savings, but is also on long-term goals such as innovation and renewal. Because of this new dual role PSM needs to balance the short-term goals referred to as exploitation, and the long-term strategic goals referred to as exploration. However, developing in-depth knowledge of the supply markets in order to achieve PSM ambidexterity is challenging, as it requires much managerial attention that is limited in nature. This research draws on the attention-based view (ABV) to study the antecedents of ambidexterity in PSM. Based on a survey of 154 Finnish manufacturing firms, a set of hypotheses was tested using structural equation modeling. The results indicate that bottom-up supply market attention has a stronger association than top-down supply market attention with all three PSM goals: exploitation, exploration and ambidexterity. PSM status is positively associated with both bottom-up and top-down supply market attention. Top management should support activities aimed at capturing supply market opportunities by ensuring that the PSM staff is not overburdened and have enough time to focus on supply market intelligence gathering and analyses. This research is among the first to study the role and enablers of attentional mechanisms that underpin ambidexterity in PSM. A contribution to the ABV theory is made by suggesting operationalizations of managerial attention constructs.

Original languageEnglish
Article number100560
Pages (from-to)1-11
JournalJournal of Purchasing and Supply Management
Issue number5
Publication statusPublished - 1 Dec 2019
MoE publication typeA1 Journal article-refereed


  • Ambidexterity
  • Attention-based view
  • Purchasing
  • Structural equation modelling


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